1

Mitotic Kinases Targeted Library

Medicinal and Computational Chemistry Dept., ChemDiv, Inc., 6605 Nancy Ridge Drive, San Diego, CA

92121 USA, Service: +1 877 ChemDiv, Tel: +1 858-794-4860, Fax: +1 858-794-4931, Email:

ChemDiv@chemdiv.com

With several successful anticancer drugs on the market and numerous compounds in clinical

developments, antimitotic agents represent an important category of anticancer agents. However, clinical

utility of the tubulin-binding agents is somewhat limited due to multiple drug resistance (MDR), poor

pharmacokinetics and therapeutic index. Another significant limitation of current modulators of tubulin

dynamics is their marginal clinical efficacy. While demonstrating impessive in vitro activity, majority of

tubulin-binding agents have not displayed antitumor activity in clinic. This fact is usually attributed to

poor balance between efficacy and toxicity, so-called therapeutic window. It is related to multiple features

of a drug including pharmacokinetics, off-target toxicity and other poorly recognized factors. In addition,

drug efflux pumps play a role in tumors developing resistance to the tubulin-binding drugs. There is

ongoing need for the modulators of other intracellular targets that result in the same anti-mitotic effect

without adverse effects of “traditional” tubulin binders. For example, kinesins, microtubule motor proteins,

play critical role in the mitotic spindle function and represent potential targets for the discovery of novel

cancer therapies1. Proteins that control cellular progression through mitosis include kinases and cysteine

proteases, namely Polo, Bub, Mad, Aurora, Cdk1, separase and others2.

Historically, researches focused on two classes of antimitotic agents (Fig. 1). The first class

includes compounds that bind reversibly to tubulin and prevent microtubule assembly and disassembly

(modulators of MT dynamics). The second class features molecules that regulate mitotic events vicariously

by interacting with specific intracellular targets such as mitotic kinesins, kinases, separase, etc.

Fig. 1. Classification of antimitotic agents and targets

Mitotic kinases

The mitotic failure is one of the essential sources of the genetic instability that hallmarks cancer

pathology. Clinical evidence suggests that numerous proteins that regulate mitosis are aberrantly expressed

2in human tumors. Regulation of mitotic progression depends on two post-translational mechanisms:

protein phosphorylation and proteolysis. The former process is mediated by mitotic kinases. Mitotic

kinases are major regulators that control mitosis progression (Table 1).

Table 1. Mitotic kinases Kinases/ Family Basic Function Mitotic Phase

Cdk1/2

(Cyclin-dependent kinase 1

and 2)

The serine-threonine kinases critical for

controlling all phases of cell cycle progression Multiple mitotic phases

Plk1

(Polo-like kinases)

Regulate chromosome segregation and

cytokinesis Multiple mitotic phases

Bub1, BubR1 and TTK/Esk Involved in chromosome segregation and

kinetochore attachment Methapase- Anaphase

Nek2/6/11

(NIMA kinases)

Control the centrosome structure during the

mitotic cell cycle

Interphase-

prometaphase,

metaphase-anaphase

Aurora A-C

(Aurora kinases)

Involved in chromosome separation, centrosome

separation and cytokinesis Multiple mitotic phases

MEN/SIN kinases

Several metazoan kinases (Ndr/LATS family

members) are structurally related to a yeast

SIN/MEN kinase (budding yeast Dbf2p/Mob1p

and fission yeast Sid2p/Mob1p), but no

functional homologies have yet been shown

Cytokinesis

MAP kinase

(Mitogen-activated kinases)

Cell cycle regulated. Many types of signal-

transduction, activates p90RSK, which in tern

activates Bub1 during Xenopus oocyte

maturation.

Interphase and

methaphase

Mps1p

(MonoPolar Spindle 1 kinase,

Dual-specificity kinase)

Implicated in the duplication of spindle pole

body Recruits checkpoint proteins at

kinetochores; Reported substrates include

Mad1, Spc110

Interphase-

promathaphase

Wee1 and Myt1 Implicated in the DNA structure checkpoints Interphase

Sid1p/2p

(Sid kinases)

Sid kinases are components of the spindle pole

body at all stages of the cell cycle and directly

implicated in cytokinesis

Cytokinesis

The mitotic cycle includes four major stages (Fig. 2). To ensure that the daughter cells receive

identical copies of the genome, progression through the cell cycle is highly regulated and controlled by

different types of mitotic kinases. For example: Cdk1, Plk1 and Nek2 regulate mitotic checkpoints at the

interphase and prophase, Cdk1 is one of the key players through the prophase-telophase, Aurora kinases

are essential to the progression of a cell through all mitotic stages.

3

Fig. 2. Mitotic kinase activity during mitotic cell cycle

As mentioned above, mitotic kinases are key players in mitotic checkpoints3. Thus, CDK1 mitotic

kinase, a nonredundant cyclin-dependent kinase (CDK), plays an essential role in the cell division,

particularly during early mitotic events (entry into mitosis). For example, loss of mitosis in tumor cells is

associated with the marked reduction in CDK1 transcription and/or loss of its active form (CDK1-P-

Thr(161))4. It occurs during G2/M transition when the activity of the dual-specificity phosphatase Cdc25C

towards Cdk1 exceeds activity of two opposing kinases Wee1 and Myt1. In turn, these proteins are

regulated by DNA structure checkpoints, which delay the onset of mitosis in the presence of unreplicated

or damaged DNA. Cdc25C is inhibited by two other kinases, Chk1 and Chk2, which are also implicated in

DNA structure checkpoint signaling pathway. Wee1 and Myt1 are upregulated by the same pathways5.

Notably, Plk1 kinase also activates Cdc25C6.

Spindle assembly checkpoint ensures accurate segregation of chromosomes during mitosis. It

blocks the anaphase stage until all chromosomes are properly attached to a bipolar mitotic spindle. Once

unstable chromosomes detected, spindle checkpoint inhibits the ubiquitin ligase activity of the anaphase-

promoting complex or cyclosome (APC/C)7. This step is reportedly mediated by proteins encoded by BUB

and MAD genes Specifically, mitotic kinases, including Bub1/3, BubR1, Bub3, Mad1, and Mad2 are

recruited to unattached kinetochores (Fig. 3)8. DNA replication and centrosome duplication are controlled

by E2F transcription factors, Mps1p kinases, cyclin A/E and Cdc20 protein9. Mitotic checkpoint protein

complexes comprised of BubR1, Bub3 and Mad2 bind to and inhibit APC/Cdc20 until all chromosomes

are properly attached to the mitotic spindle and aligned in the metaphase plate (Fig. 3A) and (3B/C))10.

4

Fig. 3. Mitotic checkpoint signaling and kinetochore attachment

The ability of a cell to track its temporal and spatial fidelity during progression through the cell

cycle is essential for survival. A spindle-positioning checkpoint has been initially described in the yeast S.

cerevisiae11. The first identified component of this step was Bub2/Bfa1 GTPase-activating protein (GAP).

It is responsible for keeping small GTPase (Tem1p) inactive until the spindle is properly oriented. The net

result is inhibition of the mitotic exit network (MEN) activation12. The signaling cascade that is

responsible for initiating MEN includes mitotic kinases that activate Cdc14p phosphatase. Cdc14p

activates APC/C/Cdh1 complex, dephosphorylates Cdk1-inhibitor Sic1p (causing its stabilization) and

transcription factor Swi5p (enhancing the production of Sic1p)13. These events lead to destruction of

mitotic cyclin–CDK complexes only when the spindle-positioning checkpoint is satisfied.

Small molecule inhibitors of mitotic kinases

Considering a pivotal role of protein phosphorylation in mitotic checkpoints, spindle function and

chromosome segregation, it is not surprising that several mitotic kinases have been implicated in

tumorigenesis. For example, CDK1-8, Aurora (Aur) (A, B, C), CDK (Cdk1, 2), Polo-like (Plk1-4), Nek

(NIMA1-11), Bub (Bub1, BubR1) and other kinases are implicated in mediation of centrosome

duplication, chromosome segregation, and cytokinesis in diverse human tumors14. These enzymes also

regulate centrosome cycle, spindle checkpoint, microtubule-kinetochore attachment, spindle assembly, and

chromosome condensation. Several potent and selective inhibitors of mitotic kinases entered clinical trials

(Table 2).

5Table 2. Small-molecule inhibitors of Polo-like and Aurora kinases in preclinical and clinical

development*

Drug name Development

phase Type of action Therapeutic area

ON-01910 1 Phase I Plk-1 inhibitor Cancer therapy

ON-1910Na 2 Phase I Plk-1 inhibitor with IC50 = 9 nM Leukemia and solid

tumors therapy

BI-2536 3 Phase I Plk-1 inhibitor Cancer therapy

Wortmannin 4 Preclinical Plks inhibitor Cancer therapy

Scytonemin 5 Preclinical Plk-1 inhibitor with IC50=2.3-3.4 µM Cancer therapy

β-Hydroxyisovalerylshikonin

(β-HIVS) 6 Preclinical Plk-1 inhibitor Cancer therapy

Staurosporine 7 Preclinical Plk-1 inhibitor with IC50 = 0.8±0.2 µM Cancer therapy

VX-680 8 Phase II

Aurora A, B and C inhibitor in vitro with

IC50 values of 0.6, 18 and 4.6 nM,

respectively

Cancer therapy

MLN-8054 9 Phase I Aurora A kinase inhibitor Solid tumors therapy

PHA-680632 10 Preclinical Aurora A and Aurora B inhibitor (IC50 = 27

and 135 nM, respectively) Cancer therapy

PHA-739358 11 Phase II Aurora-A,B and C inhibitor Cancer therapy

AZD-1152 12 Phase I Aurora-B and C inhibitor

Hematological cancer

and solid tumors

therapy

VX-528** Preclinical Aurora-B (ARK2) kinase inhibitor Cancer therapy

ZM-447439 13 Preclinical Aurora A and B kinases inhibitor with IC50

values of approximately 0.1 µM Cancer therapy

MP-235 14 Preclinical Aurora kinases A,B and C with an IC50 of

90 nM

Cancer therapy

(antiproliferative

effects in cancer cell

lines)

MP-529** Preclinical Aurora-A,B and C inhibitor Cancer therapy

Compound 15 Preclinical Aurora-A and B Kinase Inhibitor with

IC50=10.2 nM and 9 nM Cancer therapy

JNJ-7706621 16 Preclinical Aurora-A,B and C inhibitor Melanoma therapy

MKC-1260** Preclinical Aurora-A,B and C inhibitor Cancer therapy

MKC-1693 17 Preclinical Aurora-A,B and C inhibitor Cancer therapy

Compound 18 Preclinical Aurora-A and B inhibitor Cancer therapy

Compound 19 Preclinical Aurora-A (ARK1) Kinase Inhibitor Cancer therapy

Hesperadin 20 Preclinical Aurora-B; IC50= 0.25 mM Cancer therapy

SNS-314** Preclinical Aurora-A and B inhibitor Cancer therapy

CYC-116** Preclinical Aurora-A,B and C inhibitor Cancer therapy

*data at the end of 2006; ** structure is not disclosed yet.

6

Inhibitors of Polo-like kinases

Polo-like kinases (Plks) belong to a family of conserved serine/threonine kinases with a polo-box

domain, which have similar but non-overlapping functions in the cell cycle progression. Thus, they control

mitotic entry of proliferating cells and regulate many aspects of mitosis necessary for the successful

cytokinesis15. For example, they are essential for the activity of the MT organization center16. They are

important players in mitotic entry, spindle formation and cytokinesis17. Multiple Plks are present in

mammalian cells (Plk-1, Plk2/Snk, Plk3/Fnk/Prk, and Plk4/Sak) and Xenopus (Plx1-3). Of the four known

human Plks, Plk-1 is over-expressed in many tumor types. Of all mitotic kinases, Plk-1 is probably the

most validated18. Studies showed that modulation of Plk-1 activity in both transformed and normal cells

have anti-proliferative effect. Plks are deeply involved in the assembly and dynamics of the mitotic spindle

apparatus and in the activation and inactivation of CDK/cyclin complexes. In mammalian cells, Plk1

protein levels increase as cells approach M phase, with the peak of phosphorylation activity reached during

mitosis. Known substrates include Cdc25C phosphatase, cyclin B, a cohesin subunit of the mitotic spindle,

subunits of the anaphase promoting complex, and mammalian kinesin-like protein 1 MKLP-1 and other

kinesin related motor proteins. These substrates demonstrate the multiple roles of Plk1 in promoting

mitosis. Plk1 has a role in the regulation of tyrosine dephosphorylation of CDKs through phosphorylation

and activation of Cdc25C.

Cancer cells treated with the Plk inhibitors undergo apoptosis or become committed to mitotic

catastrophe. At the same time, non-transformed proliferating cells reversibly are arrested at the G2/M

boundary. In particular, small-molecule Plk inhibitors displayed selective anti-proliferative effects on

cancer cells, producing phenotypes consistent with known Plk functions19 (Fig. 4).

NHS

OCH3

OCH3

OCH3

OCH3

O

O

O O

R

1, ON-01910, R=H2, ON-1910Na, R=Na

O

O

O

OO

OO

O

CH3

CH3

H

4, Wortmannin

N

N

O

O

OH

OH

5, Scytonemin

OH

OH

O

O O

CH3

CH3

O

CH3

CH3

OH

N

NN

NNH

O

NH

NCH3

OCH3

CH3

CH3

O

3, BI-2536

6, β-HIVS

CH3

CH3

CH3

ONH

ONH

ONN

7, Staurosporine Fig. 4. Structures of small-molecule inhibitors of Polo-like Kinase-1 (Plk-1) in preclinical and clinical development

Inhibitors of Aurora kinases

7Serine/threonine protein kinases of Aurora family are involved in chromosome segregation and

cell division in all eukaryotes20. They were first identified in the cell cycle studies as Xenopus Eg221.

These enzymes are essential in the “spindle checkpoint” system used by cells to monitor fidelity of

mitosis22. Deregulation of Aurora kinases impairs spindle assembly, checkpoint function and cell division.

It causes missegregation of individual chromosomes or polyploidization accompanied by centrosome

amplification. All Aurora kinases share similar structure, with their catalytic domains flanked by very

short C-terminal tails and N-terminal domains of variable lengths23. Considering that Aurora kinases

regulate mitotic cycle progression at multiple mitotic stages (Fig. 2), they are believed to affect numerous

proteins. For example, Aurora A phosphorylates Histone H3 (S10), KSP motor protein, CPEB, PP1, D-

TACC and TPX2. Aurora B regulates activity of Histone H3(S10/S28), CENP-A, INCENP, REC-8,

MgcRacGAP, Vimentin, GFAP and Desmin24. Aurora A is localized to centrosomes from S/early G2

phases. It is required to establish a bipolar mitotic spindle25. Aurora B is associated with chromosomes in

early mitosis. In late mitosis, Aurora B migrates from centromeres to MTs at the spindle equator. As the

spindle elongates and the cell undergoes cytokinesis, Aurora B accumulates in the spindle midzone before

finally concentrating at the midbody26. Notably, all members of the Aurora-kinase family are expressed

exclusively during mitosis.

At least two isoforms, namely Auroras A and B are commonly over-expressed in human tumors,

for example in primary colon tumor samples27. Further studies suggested that they play pivotal role in

development of breast, colorectal, bladder and ovarian cancers28 (Table 3).

Table 3. Overexpression of Aurora kinases in several cancer lines and tumor tissues. The data indicate the

percentage of cell lines or tumors which overexpress kinases. Aurora kinase Cell lines/human cancers Overxpression/amplification

Aurora-A

Breast cancer cell lines

Ductal invasive carcinomas

Primary invasive breast cancers

Node-negative breast carcinomas

Primary breast carcinomas

Primary colorectal cancers

Ovarian cancer cell lines

Sporadic ovarian cancers

Hereditary ovarian cancers

Hepatic cancer cell lines

Hepatocellular carcinomas

Pancreatic carcinoma cell lines

Pancreatic cancers

30-40%

94%

29%

15%

15%

>50%

38%

44-54%

100%

100%

61%

100%

58%

Aurora-B Colorectal cancer cell lines

Primary human colorectal cancers

ND*

ND*

Aurora-C Breast cancer cell lines ND*

8Hepatocellular carcinoma cell lines

Primary human colorectal cancers

ND*

52%

* ND – No data

Aberrant expression of Aurora-A kinase leads to the genetic instability via either abnormal

centrosome duplication or defects in the spindle checkpoint29. Similarly, misregulated levels of Aurora-B

yield abnormalities in chromosome attachment or alignment to the mitotic spindle during cellular

mitosis30. Aurora-B may form complexes with Survivin, anti-apoptotic protein that is commonly

overexpressed in tumors31. It has been suggested that overexpression of Aurora B may help protect tumour

cells from apoptosis.

Since the discovery that Aurora kinases are upregulated in many tumours, several small molecule

inhibitors with sufficient selectivity for Aurora kinases were developed32. Figure 5 summarizes structures

of selected compounds.

N

N

NH NH

N

SNN

NH

O

CH3

CH38, VX-680

N N

N NH

OH

O

Cl

F

F

9, MLN-8054

N NNH

NH

X N

NO

O

CH3R

R R

10: R1=R2=Et, R3=H, X=N (PHA-680632)11: R1=R2=H, R3=OMe, X=C (PHA-739358)

NH

N

N

N

N

NH

O

O

FN

O

POOO

CH3

12, AZD-1152

NH

N

NO

OCH3N

O

NH

O

13, ZM-447439

S

NH

NH

N

N

N

N

NH

OO

S

N

N

O

O

CH3

CH3

14, MP-235

15, 418573

NH

N

S

N

N

NH

O

O

O

F

CH3N

OPOH

O

OH

16, JNJ-7706621

N

NN

O

F

FNH

SO

O

NH2

N

N

N

NH NH

N

S

NH

O

CH3

NH2

NH

ON

17, MKC-1260

NH

N

S

N

N

NH

O

O

O

F

CH3N

OH

18

NH

N

S

N

N

NH

O

O

O

Cl

CH3N

CH3

19

NH

O

NH

N

NH

SCH3O O

20, Hesperadin

1

2

3

Fig. 5. Structures of small-molecule inhibitors of Aurora kinases in preclinical and clinical development (for more information,

see table 2)

Inhibitors of Cyclin-dependent kinases

Cyclin-dependent kinases (CDK) belong to a large family of serine/threonine kinases. It is deeply

implicated in cell cycle regulation especially in early stage of mitosis. They are also involved in the

9regulation of transcription and mRNA processing. One exception is CDK9; it plays no role in cell cycle

regulation. As they are serine/threonine kinases, they phosphorylate proteins on serine and threonine

amino acid residues. A cyclin-dependent kinase is activated by association with a cyclin, forming a cyclin-

dependent kinase complex. The subfamily of CDKs includes several classes named correspondingly

CDK1-9. A cyclin-CDK complex can be regulated by several kinases and phosphatases, including Wee,

and CDK-activating kinase (CAK), and Cdc25. CAK adds an activating phosphate to the complex, while

Wee adds an inhibitory phosphate; the presence of both activating and inhibitory phosphates renders the

complex inactive. Cdc25 is a phosphatase that removes the inhibitor phosphate added by Wee, rendering

the complex active. CDK feeds back on Wee and Cdc25 to inhibit and enhance their respective activities.

CDKs are considered a potential target for anti-cancer medication. If it is possible to selectively

interrupt the cell cycle regulation in cancer cells by interfering with CDK action, the cell will die.

Currently, some CDK inhibitors such as Seliciclib are undergoing clinical trials. Although it was originally

developed as a potential anti-cancer drug, in recent laboratory tests Seliciclib 21 (Fig. 6) has also proven to

induce apoptosis in neutrophil granulocytes which mediate inflammation33. This means that novel drugs

for treatment of chronic inflammation diseases such as arthritis or cystic fibrosis could be developed.

Representative structures of small-molecule inhibitors of CDKs entered in preclinical and clinical trials or

already launched are shown in Figure 6.

NN

NN

NH

Me Me

NH

Me

O

21. Seliciclib Phase IICDK1/2/7/9 Inhibitor

N

N

O

NH2

O

N

N

MeO

MeO

22. CP-12299-1 Launched CDK1 Inhibitor

NH

NH

OO

24. NSC-105327 ClinicalCDK1/2/4/5 Inhibitor

Me

N

OH O

OH

Cl

OH O

25. Flavopiridol Phase IIICDK1/4/7/9 Inhibitor

NNO

NH

O

NMe

O

OMe26. CGP-41251 Phase IICDK1/2 Inhibitor

N

NHS

Cl

O O

SNH2

O O

23. E-7070 Phase IICDK2 Inhibitor

O

N

SMe

MeMe

S

N

NH

O

NH

27. BMS-387032 Phase I/IICDK2/7/9 Inhibitor

O O

NH

S

O

NaO

OMe

OMeMeO

MeO 2. ON-01910Na Phase I CDK1 Inhibitor

OS

O

NMe

NH

N

N

O F

F

OH

NH2

28. R-547 Phase ICDK1/2/4

Fig. 6. Structures of small-molecule inhibitors of CDKs in preclinical and clinical development

Concept and Applications

10Mitotic Kinase-targeted library design at CDL involves:

• A combined profiling methodology that provides a consensus score and decision based on various

advanced computational tools:

1. Bioisosteric morphing and funneling procedures in designing novel potential Aurora, Plk and CDK

kinase inhibitors with high IP value. We apply CDL’s proprietary ChemosoftTM software and

commercially available solutions from Accelrys, MOE, Daylight and other platforms.

2. Neural Network tools for target-library profiling, in particular Self-organizing Kohonen Maps,

performed in SmartMining Software. We have also use the Sammon mapping as a more accurate

computational tool to create our kinase-focused library.

3. A molecular docking approach to focused library design.

4. Computational-based `in silico` ADME/Tox assessment for novel compounds includes prediction of

human CYP P450-mediated metabolism and toxicity as well as many pharmacokinetic parameters, such as

Brain-Blood Barrier (BBB) permeability, Human Intestinal Absorption (HIA), Plasma Protein binding

(PPB), Plasma half-life time (T1/2), Volume of distribution in human plasma (Vd), etc.

The fundamentals for these applications are described in a series of our recent articles on the design

of exploratory small molecule chemistry for bioscreening [for related data visit ChemDiv. Inc. online

source: www.chemdiv.com].

• Synthesis, biological evaluation and SAR study for the selected structures:

1. High-throughput synthesis with multiple parallel library validation. Synthetic protocols, building blocks

and chemical strategies are available.

2. Library activity validation via bioscreening (the synthesized compounds should be tested jointly against

both Aurora and Plk kinases due to their similarity in binding site composition). SAR is implemented in

the next library generation.

We practice a multi-step approach for building Mitotic Kinase-focused library:

Virtual screening

Choosing structures that are most likely to have a predefined target-specific activity of interest

from the vast assortment of structurally dissimilar molecules is a particular challenge in compound

selection. This challenge has been tackled with powerful computational methodologies, such as docking

available structures into the receptor site and pharmacophore searching for particular geometric relations

among elements thought critical for biological activity. Both methodologies focus on conformational

flexibility of both target and ligand, which is a complex and computationally intense problem. The latest

developments in this field pave the way to wide industrial application of these technologies in drug design

and discovery, though the limits of computational power and time still restrict the practical library size

selected by these methods.

11Another popular approach to VS is based on ligand structure and consists of selecting

compounds structurally related to hits identified from the initial screening of the existing commercial

libraries and active molecules reported in research articles and patents. Although broadly used in the

development of SAR profiling libraries, these methods usually perform poorly when it comes to the

discovery of structurally novel lead chemotypes.

An alternative design for target-specific libraries is based on statistical data mining methods, which

are able to extract information from knowledge databases of active compounds.

Structure-based design

At the initial stage of our approach, we have collected a unique database which contains more than

22 thousand of known drugs and compounds which have been entered into various preclinical or clinical

trials. Each compound in this database is characterized by a defined profile of target-specific activity,

focused against 1 of more than 100 different protein targets. The database was filtered based on MW (not

more than 800). Molecular features encoding the relevant physicochemical and topological properties of

compounds were calculated from 2D molecular representations and selected by PCA. These molecular

descriptors encode the most significant molecular features, such as molecular size, lipophilicity, H-binding

capacity, flexibility, and molecular topology. Taken in combination, they define both pharmacokinetic and

pharmacodynamic behavior of compounds and are effective for property-based classification of target-

specific groups of active agents.

A Kohonen SOM (14×14) of 22,110 pharmaceutical leads and drugs generated as a result of the

unsupervised learning procedure is depicted in Figure 6. It shows that the studied compounds occupy a

wide area on the map, which can be characterized as the area of drug-likeness. Distribution of various

target-specific groups of ligands within the Kohonen map demonstrates that most of these groups have

distinct locations in specific regions of the map (Figure 6a through Figure 6e).

(a) (b) (c) (d) (e) Fig. 6. (a) Property space of 22,110 pharmaceutical leads and drugs visualized using the Kohonen map. Distribution of five

target-specific groups of pharmaceutical agents: (b) GPCR agonists/antagonists; (c) tyrosine kinase inhibitors; (d) p38 MAPK

inhibitors; (e) serine/threonine kinese inhibitors including Plk, Aurora and CDK kinases

A possible explanation of these differences is in the fact that, as a rule, receptors of one type share

a structurally conserved ligand-binding site. The structure of this site determines molecular properties that

12a receptor-selective ligand should possess to properly bind the site. These properties include

specific spatial, lipophilic, and H-binding parameters, as well as other features influencing the

pharmacodynamic characteristics. Therefore, every group of active ligand molecules can be characterized

by a unique combination of physicochemical parameters differentiating it from other target-specific groups

of ligands. Another explanation of the observed phenomenon can be related to different pharmacokinetic

requirements to drugs acting on different biotargets.

During the initial stage of our focused-library design we have effectively used this model to select

structures which are the most promising towards Polo-like, Aurora and CDK kinases.

Target-based Design

Based on the data derived from PDB Protein Data Bank34 we have further construct and effectively

applied molecular docking models to select the structures of paramount interest within the scope of our

focused-library design. Molecular docking of the selected structures (see the section above) was performed

using Surflex Docking computational program Version 1.24 (BioPharmics LLC). After the generation of

protomol all structures were docked into the active binding site of Plk, Aurora and CDK kinases. Ten

conformations for each structure were generated and docked into the binding site. There are two scores for

each conformation docked: an affinity (-log(Kd)) (named as “polar”) and a “penetration score” (arbitrary

units named as “penetration”). The penetration score is the degree of ligand penetration into the active site

of protein studied. Thus, penetration scores that are close to 0.0 are favorable however visual analysis of

each conformer is more preferable. The examples of developed docking models are shown in Fig. 7.

(a) (b) (c) (d)

(e) (f) (g) Fig. 7. The developed docking models based on: (a) crystal structure of Aurora-A kinase in complex with VX-680 (8)35; (b)

crystal structure of Aurora-2 kinase in complex with PHA-739358 (11)36; (c) crystal structure of Polo-like kinase-1 catalytic

13domain in complex with Wortmannin (4)37; (d) Human cyclin- dependent kinase 2 (hCDK2) in complex with Seliciclib

(21)38. Representative compounds from our kinase-targeted library docked into the binding site of (e) Polo-like kinase

(compound Plk-T-2), (f) Aurora kinase (compound Aur-T-1) and (g) CDK (compound CDK-T-3), their structures see below

For example, as shown in Fig. 7, key structural elements and atoms of Wortmannin as well as

principal interactions within active site of an activated Plk-1 are significantly similar to compound Plk-T-2

from our focused-library.

It should be particularly noted that the catalytic domain of Plk-1 shares significant primary amino-

acid homology and structural similarity with Aurora-A kinase. Therefore, biological screening against

Aurora-A may provide a valuable source for compounds also active against Plk classes, especially Plk1.

This suggestion has been strongly supported in a recent paper by Elling and colleagues39.

Based on the obtained results we can reasonably conclude that all of the tested compounds from

our focused-library are potential inhibitors of Polo-like, Aurora and CDK kinases.

Synthesis and biological evaluation

(4) Novel Mitotic kinase-targeted library is synthesized according to the above criteria.

(5) The subsets of Mitotic kinase library which includes both Aurora, Polo-like and CDK kinase-targeted

compounds are validated by bioscreening in collaboration with academic institutions.

Our strategy has proven to be efficient for generation of protein class-targeted libraries. The higher

hit rate over diverse libraries, along with identification of novel active chemotypes with optimized

diversity and ADME properties, has been shown in multiple studies. Using the computational approaches

listed above we have compiled Mitotic kinase-focused library consisted of about 10K small molecule

compounds Representative set of Mitotic kinase-biased compounds is shown below.

N

N

N

N

NH

O

CH3

CH3CH3

CH3

N

N

N

N

NH

O

O

O

OH

O

O CH3

CH3

CH3

SO

ONH

O

O O

CH3

CH3

CH3

N

N

NH

N

O

NH

O

CH3

N

N

NH

O

O

O

Cl

CH3

CH3

CH3

N

N

N

N

N

O

CH3

CH3

NN N

SNH O

OO

NH2CH3

F

N

NN

N

NH

CH2

N

N

O

N N

O

O

NH2

O

O

CH3

CH3

NNH

NO

N

S

NO

CH3 Examples of compounds from the Mitotic kinase-targeted library

14Conclusion

Among a variety of anticancer drugs launched on the market and numerous compounds in

preclinical and clinical development, modulators of microtubule dynamics remain to be the most important

class of anti-mitotic agents. However, there are significant limitations associated with their utility. These

include: drug resistance caused by mutations in β-tubulin and multiple drug resistance (MDR), toxicity,

poor pharmacokinetics and poor therapeutic index40. These issues led to identification of an alternative

targets and signaling mechanisms that yield anti-mitotic effect with greater specificity and more

predictable pharmacology. Mitotic kinases represent large and relatively unexplored class of antimitotic

targets. These proteins are implicated at multiple stages in the mitosis and cytokinesis. Among them Polo-

like, Aurora and CDK kinases are the key regulators of a majority of mitotic checkpoints. Mps1p kinase

has been implicated in the duplication of a spindle pole body and spindle assembly checkpoint41. Nek2

kinase (NIMA family) promotes centrosome separation and may control histone H3 phosphorylation42.

MAP kinases regulate spindle dynamics and chromosome movement43. Mad (1p, 2p and 3p) proteins are

involved in a spindle assembly checkpoint mechanism44. Mitotic kinases are critical for the mitotic exit45

and cytokinesis46. CDK1 kinase still remains to be one of the main enzymes in mitosis. Discovery of novel

agents acting at specific phases of the mitotic cycle will allow clearer definition of the relationships

between discrete mechanical phases of spindle function, regulation of cell-cycle progression and

programmed cell death.

Thus, here we provide efficient tools for in silico design of novel small molecule inhibitors of the

title mitotic kinases. Based on the accumulated knowledgebase as well as unique structure- and target-

based models we have been designed about 10K small molecule compounds targeted specifically against

Polo-like, Aurora and CDK kinases. As a result, the library is renewed each year, proprietary compounds

comprising 50-75% of the entire set. Clients are invited to participate in the template selection process

prior to launch of our synthetic effort.

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